Functional characterization of hyperpolarization-activated cyclic nucleotide-gated channels in rat pancreatic β cells
Bibliographic record
Abstract
Hyperpolarization-activated cyclic nucleotide-gated (HCN) channels regulate pacemaker activity in some cardiac cells and neurons. In the present study, we have identified the presence of HCN channels in pancreatic beta-cells. We then examined the functional characterization of these channels in beta-cells via modulating HCN channel activity genetically and pharmacologically. Voltage-clamp experiments showed that over-expression of HCN2 in rat beta-cells significantly increased HCN current (I(h)), whereas expression of dominant-negative HCN2 (HCN2-AYA) completely suppressed endogenous I(h). Compared to control beta-cells, over-expression of I(h) increased insulin secretion at 2.8 mmol/l glucose. However, suppression of I(h) did not affect insulin secretion at both 2.8 and 11.1 mmol/l glucose. Current-clamp measurements revealed that HCN2 over-expression significantly reduced beta-cell membrane input resistance (R(in)), and resulted in a less-hyperpolarizing membrane response to the currents injected into the cell. Conversely, dominant negative HCN2-AYA expression led to a substantial increase of R(in), which was associated with a more hyperpolarizing membrane response to the currents injected. Remarkably, under low extracellular potassium conditions (2.5 mmol/l K(+)), suppression of I(h) resulted in increased membrane hyperpolarization and decreased insulin secretion. We conclude that I(h) in beta-cells possess the potential to modulate beta-cell membrane potential and insulin secretion under hypokalemic conditions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".